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Markus Holtz - Sparse Grid Quadrature in High Dimensions with Applications in Finance and Insurance - 9783642265631 - V9783642265631
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Sparse Grid Quadrature in High Dimensions with Applications in Finance and Insurance

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Description for Sparse Grid Quadrature in High Dimensions with Applications in Finance and Insurance Paperback. Series: Lecture Notes in Computational Science and Engineering. Num Pages: 200 pages, 32 black & white illustrations, biography. BIC Classification: KF; PBKS. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 10. Weight in Grams: 288.
This book deals with the numerical analysis and efficient numerical treatment of high-dimensional integrals using sparse grids and other dimension-wise integration techniques with applications to finance and insurance. The book focuses on providing insights into the interplay between coordinate transformations, effective dimensions and the convergence behaviour of sparse grid methods. The techniques, derivations and algorithms are illustrated by many examples, figures and code segments. Numerical experiments with applications from finance and insurance show that the approaches presented in this book can be faster and more accurate than (quasi-) Monte Carlo methods, even for integrands with hundreds of dimensions.

Product Details

Format
Paperback
Publication date
2012
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
200
Condition
New
Series
Lecture Notes in Computational Science and Engineering
Number of Pages
192
Place of Publication
Berlin, Germany
ISBN
9783642265631
SKU
V9783642265631
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

About Markus Holtz
• Scientific employee at the Institute for Numerical Simulation at the University of Bonn (July 2004 - January 2009) • Involved in several teaching activities and research projects in the area of computational finance partly in close cooperation with financial institutions • Since January 2009 at head office of Baloise Group working on the introduction of stochastic models for life ... Read more

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